Smart Data Collective

FEBRUARY 2, 2021

Also, thanks to Big Data, recruitment is now more accurate. Keep in mind that recruitment agencies have to deal with huge volumes of unstructured data, and analyzing all this data by traditional means is not only slow, but also ineffective.

Big Data 84

Big Data Recreation/Entertainment Cost-Benefit Finance 84

Sisense

MAY 28, 2020

Product teams are already having to manage the growing complexities that come with modern data environments. Chandana Gopal, Business Analytics Research Director, IDC. Teams should look to deliver measurable value with short term projects to build business cases for more expensive or longer projects.”

Internet of Things 83

Internet of Things Metadata Data-driven Unstructured Data 83

Sisense

NOVEMBER 12, 2020

Cloud data warehouses took the benefits of the cloud and applied them to data warehouses — bringing massive parallel processing to data teams of all sizes. Scaling the warehouse as business analytics needs grow is as simple as clicking a few buttons (and in some cases, it is even automatic).

Data Warehouse 52

Data Warehouse Data Lake OLAP Data-driven 52

Rita Sallam

JULY 22, 2016

And here we are now, past the tipping point of a more than 10 to 11 year transition away from IT-centric reporting platforms to modern BI and analytics platforms that make up much of the new buying in the BI and Analytics market. Q2: Would you consider Sisense better than others in handling big and unstructured data?

Analytics 40

Analytics Business Intelligence Metadata Statistics 40

CIO Business Intelligence

MARCH 9, 2022

As a result, users can easily find what they need, and organizations avoid the operational and cost burdens of storing unneeded or duplicate data copies. Newer data lakes are highly scalable and can ingest structured and semi-structured data along with unstructured data like text, images, video, and audio.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Data Quality 119

BizAcuity

APRIL 14, 2022

Big Data technology in today’s world. Did you know that the big data and business analytics market is valued at $198.08 Or that the US economy loses up to $3 trillion per year due to poor data quality? quintillion bytes of data which means an average person generates over 1.5 billion in 2020?

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

Grooper

AUGUST 19, 2019

Modern era business stakeholders need current and relevant insights from across business units and processes. Traditional data sources like end of month statements and quarterly reports are no longer enough. Access to enterprise-wide information fuels analytics solutions and enable a new approach for decision making.

Analytics 54

Analytics Machine Learning Data Science Data-driven 54

Sisense

DECEMBER 12, 2019

Getting value from that data is the key to surviving and thriving in the future. The 4 signs include: Reporting is done manually in Excel and is time consuming Difficulty pulling and joining data from multiple data sources Inability to access and utilize the data collected to see insights Need for data visualization in real time.

Business Intelligence 88

Business Intelligence Software Data-driven Visualization 88

datapine

FEBRUARY 22, 2022

Find out what is working, as you don’t want to totally scrap an already essential report or process. What data analysis questions are you unable to currently answer? You should be continually measuring and refining your processes, data and reports. On the flip side, document everything that isn’t working.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

IBM Big Data Hub

AUGUST 4, 2023

Data within a data fabric is defined using metadata and may be stored in a data lake, a low-cost storage environment that houses large stores of structured, semi-structured and unstructured data for business analytics, machine learning and other broad applications.

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59

Jet Global

MAY 9, 2024

A data pipeline is a series of processes that move raw data from one or more sources to one or more destinations, often transforming and processing the data along the way. Data pipelines support data science and business intelligence projects by providing data engineers with high-quality, consistent, and easily accessible data.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52